Bacterial cell segmentation and imaging processing

Water is essential to life, 72% of the planet earth is covered in water. However, less than 1% is available for drinking, industry and nature. 1 ml of drinking water on average contains 80,000 of bacteria, and some are harmful to human body such as Cryptosporidium, E.coli, Giardia, Hepatitis A, Legi...

Full description

Saved in:
Bibliographic Details
Main Author: Gao, Peiji
Other Authors: Liu Aiqun
Format: Final Year Project
Language:English
Published: 2019
Subjects:
Online Access:http://hdl.handle.net/10356/78017
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-78017
record_format dspace
spelling sg-ntu-dr.10356-780172023-07-07T17:45:59Z Bacterial cell segmentation and imaging processing Gao, Peiji Liu Aiqun Muhammad Faeyz Karim School of Electrical and Electronic Engineering DRNTU::Engineering::Computer science and engineering::Software::Programming languages Water is essential to life, 72% of the planet earth is covered in water. However, less than 1% is available for drinking, industry and nature. 1 ml of drinking water on average contains 80,000 of bacteria, and some are harmful to human body such as Cryptosporidium, E.coli, Giardia, Hepatitis A, Legionella pneumophila, and Salmonella. Consumption of raw water may cause disease or even death due to waterborne bacterial infection. Monitoring of the water quality is necessary and crucial. My project focus on the detection of Cryptosporidium and Giardia as these microorganisms will highly cause the outbreak of diseases. Cytometer will be used to detect and photograph the various particles found in preconcentrated sample of drinking water, the liquid mixture with sample and fluid is injected into the flow cytometer instrument, ideally the cell will flow through the laser beam one by one and the light scattered is characteristic to the cells and their components. With this flow cytometry technology, thousands of cells can be examined in short time. However, the basic characteristic have to be measured and collated manually. Manual labelling requires the lab user to have the relevant expertise to handle the detection process and measure the samples individually. Repetition of this process and long operation time may lead to human error, this can affect the accuracy of the data and efficiency of the measurement process. With this algorithm implantation, the characteristic of the bacterial image will be measure automatically and collated into excel file for further usage. Follow by the user interface design, the designed software reduce the disadvantage of manual measurement and enhance the data accuracy as well. Bachelor of Engineering (Electrical and Electronic Engineering) 2019-06-11T04:00:00Z 2019-06-11T04:00:00Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/78017 en Nanyang Technological University 45 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Software::Programming languages
spellingShingle DRNTU::Engineering::Computer science and engineering::Software::Programming languages
Gao, Peiji
Bacterial cell segmentation and imaging processing
description Water is essential to life, 72% of the planet earth is covered in water. However, less than 1% is available for drinking, industry and nature. 1 ml of drinking water on average contains 80,000 of bacteria, and some are harmful to human body such as Cryptosporidium, E.coli, Giardia, Hepatitis A, Legionella pneumophila, and Salmonella. Consumption of raw water may cause disease or even death due to waterborne bacterial infection. Monitoring of the water quality is necessary and crucial. My project focus on the detection of Cryptosporidium and Giardia as these microorganisms will highly cause the outbreak of diseases. Cytometer will be used to detect and photograph the various particles found in preconcentrated sample of drinking water, the liquid mixture with sample and fluid is injected into the flow cytometer instrument, ideally the cell will flow through the laser beam one by one and the light scattered is characteristic to the cells and their components. With this flow cytometry technology, thousands of cells can be examined in short time. However, the basic characteristic have to be measured and collated manually. Manual labelling requires the lab user to have the relevant expertise to handle the detection process and measure the samples individually. Repetition of this process and long operation time may lead to human error, this can affect the accuracy of the data and efficiency of the measurement process. With this algorithm implantation, the characteristic of the bacterial image will be measure automatically and collated into excel file for further usage. Follow by the user interface design, the designed software reduce the disadvantage of manual measurement and enhance the data accuracy as well.
author2 Liu Aiqun
author_facet Liu Aiqun
Gao, Peiji
format Final Year Project
author Gao, Peiji
author_sort Gao, Peiji
title Bacterial cell segmentation and imaging processing
title_short Bacterial cell segmentation and imaging processing
title_full Bacterial cell segmentation and imaging processing
title_fullStr Bacterial cell segmentation and imaging processing
title_full_unstemmed Bacterial cell segmentation and imaging processing
title_sort bacterial cell segmentation and imaging processing
publishDate 2019
url http://hdl.handle.net/10356/78017
_version_ 1772826549749284864